Movement Analysis Software for Telemetry (MAST) for use in removing false positive and overlap detections from radio telemetry projects and assessing 1D movement patterns
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Modify the prior to account for codset crowding #10
It has come to my attention that the more crowded a codeset gets the less opportunity there is to detect a known false positive. We've discussed this operationally (i.e. add frequencies to monitor to feed the training data). However when one frequency is scanned and it has, say, 20% of the codeset filled with valid tags there's a lot more room to detect false positives than when 80% of the codeset is filled. I suggest we apply a simple correction to the priors to accommodate this. The user will have to know what their codeset limits are. ALTERNATIVELY, we could put in a general scalar that could be used in a similar way. That way if we want to use the prior but increase or decrease the weight we could add that in.
It has come to my attention that the more crowded a codeset gets the less opportunity there is to detect a known false positive. We've discussed this operationally (i.e. add frequencies to monitor to feed the training data). However when one frequency is scanned and it has, say, 20% of the codeset filled with valid tags there's a lot more room to detect false positives than when 80% of the codeset is filled. I suggest we apply a simple correction to the priors to accommodate this. The user will have to know what their codeset limits are. ALTERNATIVELY, we could put in a general scalar that could be used in a similar way. That way if we want to use the prior but increase or decrease the weight we could add that in.